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- Tasks: Join us as a Data Scientist II, tackling real estate data challenges and driving innovation.
- Company: Zonda is revolutionising the housing industry with a bold vision for 2030.
- Benefits: Enjoy remote work, competitive salary, wellness programs, and career growth opportunities.
- Why this job: Make a real impact in a diverse, collaborative team while learning about data and real estate.
- Qualifications: Bachelor's degree and 3+ years in Data Science; proficiency in Python and SQL required.
- Other info: We value diversity and are committed to inclusion in our hiring process.
The predicted salary is between 36000 - 60000 £ per year.
Remote, Glasgow, UK| Full-Time
Zonda is redefining the future of housing. We are perfectly placed in the heart of the fast-growing real estate industry. We are making big bets on the future of real-estate, trailblazing a 2030 vision for the industry. Here at Zonda, you’ll be able to use your passion and curiosity to drive the next generation of real estate analysts, advisors, technologists, and marketers.
Zonda is looking for a passionate Data Scientist II to help create, evolve and expand our team. Zonda looks for people who can grow, think, dream, and create. When you join our team, you’ll be in a unique position to make a change with every project. You’ll use your full range of skills to build great relationships and experiences and learn about the real estate industry, economics, marketing and data. You’ll be supported with the necessary tools, and you\’ll be working with an awesome and like-minded team. Our teams are innovative, diverse, multidisciplinary, and collaborative – all working to build the future of housing.
The Data Scientist II is a mid-level position responsible for Data Science and modelling in the realm of housing data. The Data Scientist would achieve this through the application of established processes of data analytics, experiments, engaging with stakeholders with the findings and subsequently developing code for production. This will involve working with other data scientists or ML Engineers and business stakeholders. This role requires good cross disciplinary skills across databases, analytics, statistics, and modelling. The person should be able to work independently in a DevOps environment, often collaborating with stakeholders from other technical teams as well as business teams. Good communication skills with an ability to demystify ML algorithms and capabilities is a must, as stakeholders in ML products include software engineering teams as well as non-technical business partners.
Responsibilities:
- Collection, cleaning, and pre-processing of data for solving business problems.
- Conduct exploratory data analysis to identify trends, patterns, and correlations in the data.
- Develop statistical and machine learning models for data quality improvements, predictions, segmentation, and imputation.
- Engage business stakeholders from analysis using visualisations and findings.
- Collaborate with stakeholders to define requirements and deliverables.
- Ownership of documentation related to datasets, model selection, training experiments, and production infrastructure.
- Monitor ML models in production, setting metrics to identify drift, and establish corrective measures for restoring model performance.
- Identify and implement appropriate tools for monitoring product performance in inference.
- Continual learning and self-improvement with a focus on latest trends, techniques, and best practices in Data Science and Machine Learning.
Requirements:
- Bachelor\’s degree in computer science, Statistics, Mathematics, or a related field.
- 3+ years of experience in Data Science, Data Analytics, Machine learning, or a related field.
- Proficient in Python and working knowledge of libraries NumPy, Pandas, Matplotlib, and scikit-learn etc.
- Proficient in SQL for data extraction, transformation and analysis.
- Strong mathematical, analytical, and problem-solving skills.
- Strong understanding of statistical modelling, hypothesis testing and sampling methods.
- Understanding of dataset preparation, splits, data quality control, and management.
- Knowledge of data pre-processing and feature engineering techniques.
- Sound understanding of software development best practices and DevOps.
- Experience with version control systems like Git.
- Experience with cloud computing platforms like AWS, Google Cloud, or Azure.
- Knowledge and implementation of advanced data visualisation techniques.
- Excellent communication and teamwork skills.
Nice to have
- Masters in a specific field such as Statistics, Data Science, Machine Learning, or AI.
- Familiarity with containerization and orchestration tools like Docker, Airflow, Kubernetes etc.
- Familiarity with data pipelines and associated tools like dbt .
- Experience with cloud-based data science tools such as AWS Sagemaker .
- Basic understanding of housing market, housing economics, mortgages, and housing construction.
- Familiarity with building and maintaining APIs with standard tools such as FastAPI or Flask.
Why People Love Working Here
- We offer meaningful work and opportunities for career growth
- Interesting product roadmap with room for innovation
- Competitive Salary
- Employee Assistance Program (EAP)
- Live Meditation Sessions
- Employee Recognition Platform
- Virtual Wellness Program
- Visionary Leadership Team
Inclusion & Equal Opportunity Employment
Zonda (formerly Hanley Wood | Meyers Research) is proud to be an Equal Opportunity Employer committed to diversity, inclusion & belonging. Here at Zonda, we are interested in every qualified candidate who is eligible to work in the United Kingdom. #J-18808-Ljbffr
Data Scientist II employer: Zonda
Contact Detail:
Zonda Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist II
✨Tip Number 1
Familiarise yourself with the latest trends in data science and machine learning, especially those relevant to the real estate industry. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Showcase your ability to communicate complex data insights clearly. Prepare examples of how you've successfully presented data findings to non-technical stakeholders, as this is a key requirement for the Data Scientist II role.
✨Tip Number 3
Network with professionals in the real estate and data science fields. Attend relevant webinars or local meetups to connect with others who might provide insights or referrals that could help you land the job.
✨Tip Number 4
Demonstrate your proficiency in Python and SQL through practical projects or contributions to open-source initiatives. Having tangible evidence of your skills can set you apart from other candidates.
We think you need these skills to ace Data Scientist II
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in Data Science, particularly focusing on your skills in Python, SQL, and machine learning. Use keywords from the job description to align your qualifications with what Zonda is looking for.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data science and the real estate industry. Mention specific projects or experiences that demonstrate your ability to solve business problems using data analytics and modelling.
Showcase Your Technical Skills: In your application, provide examples of your proficiency with tools and libraries mentioned in the job description, such as NumPy, Pandas, and cloud platforms like AWS. Consider including links to any relevant projects or GitHub repositories.
Highlight Communication Skills: Since good communication is essential for this role, include examples of how you've effectively communicated complex data findings to non-technical stakeholders in previous positions. This will demonstrate your ability to engage with diverse teams.
How to prepare for a job interview at Zonda
✨Showcase Your Technical Skills
Make sure to highlight your proficiency in Python and relevant libraries like NumPy and Pandas. Be prepared to discuss specific projects where you've applied these skills, as well as your experience with SQL for data extraction and analysis.
✨Demonstrate Your Problem-Solving Abilities
Prepare examples of how you've tackled complex data problems in the past. Discuss your approach to exploratory data analysis and how you identified trends or patterns that led to actionable insights.
✨Communicate Clearly with Stakeholders
Since good communication is key, practice explaining technical concepts in simple terms. Be ready to share how you've engaged with non-technical stakeholders in previous roles and how you presented your findings effectively.
✨Stay Updated on Industry Trends
Zonda values continual learning, so be prepared to discuss recent developments in data science and machine learning. Mention any courses, workshops, or resources you've used to stay current, especially those related to real estate analytics.
